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Posted to issues@spark.apache.org by "Maciej Bryński (JIRA)" <ji...@apache.org> on 2016/01/13 22:13:40 UTC

[jira] [Comment Edited] (SPARK-9850) Adaptive execution in Spark

    [ https://issues.apache.org/jira/browse/SPARK-9850?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15096985#comment-15096985 ] 

Maciej Bryński edited comment on SPARK-9850 at 1/13/16 9:13 PM:
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[~matei]
Hi,
I'm not sure if my issue is related to this Jira.

In 1.6.0 when using sql limit Spark do following:
- execute limit on every partition
- then take result

Is it possible to finish scanning partitions when we collect enough rows for limit ?


was (Author: maver1ck):
[~matei]
Hi,
I'm not sure if my issue is related to this Jira.

In 1.6.0 when using sql limit Spark do following:
- execute limit on every partition
- then take result
Is it possible to finish scanning partitions when we collect enough rows for limit ?

> Adaptive execution in Spark
> ---------------------------
>
>                 Key: SPARK-9850
>                 URL: https://issues.apache.org/jira/browse/SPARK-9850
>             Project: Spark
>          Issue Type: Epic
>          Components: Spark Core, SQL
>            Reporter: Matei Zaharia
>            Assignee: Yin Huai
>         Attachments: AdaptiveExecutionInSpark.pdf
>
>
> Query planning is one of the main factors in high performance, but the current Spark engine requires the execution DAG for a job to be set in advance. Even with cost-based optimization, it is hard to know the behavior of data and user-defined functions well enough to always get great execution plans. This JIRA proposes to add adaptive query execution, so that the engine can change the plan for each query as it sees what data earlier stages produced.
> We propose adding this to Spark SQL / DataFrames first, using a new API in the Spark engine that lets libraries run DAGs adaptively. In future JIRAs, the functionality could be extended to other libraries or the RDD API, but that is more difficult than adding it in SQL.
> I've attached a design doc by Yin Huai and myself explaining how it would work in more detail.



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